[Eeglablist] Frontiers in Neuroengineering: Interaction of BCI with the underlying neurological conditions in patients: pros and contras

[Aleksandra Vuckovic]

Dear EEG lab community
I would like to invite you to contribute to a special issue of Frontiers in Neuroengineering 'Interaction of BCI with the underlying neurological conditions in patients: pros and contras'. http://www.frontiersin.org/neuroengineering/researchtopics/interaction_of_bci_with_the_un/2020
Deadline for the Abstract submission is 31st August and the deadline for the full paper submission is 31st October 2013.

Regards,
Aleksandra Vuckovic, PhD Biomed
Lecturer in Rehabilitation Engineering
Centre for Rehabilitation Engineering, University of Glasgow, UK


Interaction of BCI with the underlying neurological conditions in patients: pros and contras'

The primary purpose of Brain Computer Interface (BCI) systems is to help patients to communicate with their environment or to aid to their recovery. A common denominator for all BCI patient groups is that they all suffer from a neurological deficit. As a consequence BCI systems in clinical settings operate with control signals (brain waves) which could be substantially altered compared to brain waves of able-bodied individuals.

Most BCI systems are built and tested on able-bodied people, suffering from insufficient robustness to be used on patients. One of the reasons for that is a lack of systematic analysis on how different neurological problems, often present in clinical BCI users affect performances of BCI. While there is an awareness that loss of sensory and motor functions affects BCI performance through disuse reorganization of the sensory and motor cortex, little is known about the effect of other neurological deficits on BCI performance.

Examples of these deficits are : neuropathic pain, chronic nociceptive pain, spasticity and antispastic drugs, loss of cognitive functions, drowsiness caused by medications, medications which are increasing/decreasing brain activity in certain frequency range, epilepsy (not BCI users but often used to test ECoG based BCI) .

While some of these deficits may decrease performance of a BCI, others may potentially improve it (e.g. overactivation of motor cortex in patients with Central neuropathic pain (CNP) causing stronger responses during imagination of movement, thus potentially improving BCI performance).

Some BCI methods are based on neurofeedback (operant conditioning) which can in a long term cause plastic changes, with positive or detrimental effects. An important aspect, almost completely absent from BCI research is analysis of potential adverse effect of long term BCI on the underlying neurological problems.
An example of this is again CNP, present in most potential BCI users with chronic condition (spinal cord injury 40%, multiple sclerosis 27%, Parkinson's disease 10%, stroke 8%) . While there are evidences from pain research studies that prolonged motor imagery increases CNP, chronic pain has never been discussed in the light of BCI.
Thus some types of BCI might be more suitable for use in rehabilitation of recently injured patients than for communication and control.
For example research in our lab on chronic paraplegic patients with and without CNP indicates that CNP improves performance of motor imagery based BCI but causes discomfort. However we use motor imagery based BCI to promote recovery of hand function in acute tetraplegic patients.

The aim of this special issue is to getter evidence and raise awareness of how BCI systems based on different principles (SSVEP, P300, slow cortical potential, auditory potential, NIRS, slow cortical potential ECoG) interact with the underlying neurological problems. This would generate body of knowledge that would be valuable not only for researchers working in clinical setting but also for a vast majority of BCI researchers in Computer Engineering departments who develop and test new algorithms on able-bodied people. This should contribute building more robust or tailor made BCI protocols, facilitating translation of research from laboratories to the end users.

The proposed list of contributors includes mainly rechearchers who published BCI studies on patients.


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